Closed ilkersigirci closed 11 months ago
Hi ilker, I got a problem when I tokenize smiles seq, And I found that in you example smiles has the Cl
atom. So I want to konw if you meet the same question.
The Iuput seq is COC1=C(C=C2C(=C1)CCN=C2C3=CC(=C(C=C3)Cl)Cl)Cl
However the output of tokenizer incorrectly labeled the Cl
as C
, I don't konw how the fix it. And I also found that in the ChenBERTa token table, it indeed has the 'Cl' token.
The output of the tokenize() result as follow:
['C', 'O', 'C', '1', '=', 'C', '(', 'C', '=', 'C', '2', 'C', '(', '=', 'C', '1', ')', 'C', 'C', 'N', '=', 'C', '2', 'C', '3', '=', 'C', 'C', '(', '=', 'C', '(', 'C', '=', 'C', '3', ')', 'C', ')', 'C', ')', 'C']
Firstly, thanks for open sourcing the model. I want to cluster SMILES compounds by using their pretrained model vectors. I have implemented following code for this but it doesn't work for more than 1000 row data. Idk if I am doing this correctly since I haven't seen any official documentation for this. The only relatable code part in the repo is viz_utils.gen_embeddings function. Unfortunately it also suffers from larger SMILES dataset size
I am open to suggestions. Thank in advance.